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Kinase-substrate Edge Biomarkers Provide a More Accurate Prognostic Prediction in ER-negative Breast Cancer.
Sun, Yidi; Li, Chen; Pang, Shichao; Yao, Qianlan; Chen, Luonan; Li, Yixue; Zeng, Rong.
Afiliação
  • Sun Y; CAS Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Shanghai 200031, China.
  • Li C; CAS Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • Pang S; Deptartment of Statistics, School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Yao Q; School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Chen L; CAS Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Department of Life Sciences, ShanghaiTech University, Shanghai 201
  • Li Y; School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China; Department of Life Sciences, ShanghaiTech University, Shanghai 201210, China; Bio-Med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shang
  • Zeng R; CAS Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Department of Life Sciences, ShanghaiTech University, Shanghai 201
Genomics Proteomics Bioinformatics ; 18(5): 525-538, 2020 10.
Article em En | MEDLINE | ID: mdl-33450402
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: Genomics Proteomics Bioinformatics Assunto da revista: BIOQUIMICA / GENETICA / INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China País de publicação: China
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: Genomics Proteomics Bioinformatics Assunto da revista: BIOQUIMICA / GENETICA / INFORMATICA MEDICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China País de publicação: China